Overview

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Dataset statistics

Number of variables15
Number of observations930
Missing cells0
Missing cells (%)0.0%
Duplicate rows15
Duplicate rows (%)1.6%
Total size in memory109.1 KiB
Average record size in memory120.1 B

Variable types

Categorical3
Text11
Numeric1

Alerts

Dataset has 15 (1.6%) duplicate rowsDuplicates

Reproduction

Analysis started2025-06-19 19:34:12.207508
Analysis finished2025-06-19 19:34:13.623895
Duration1.42 second
Software versionydata-profiling vv4.16.1
Download configurationconfig.json

Variables

Company Name
Categorical

Distinct19
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size7.4 KiB
Oppo
129 
Apple
97 
Honor
91 
Samsung
88 
Vivo
86 
Other values (14)
439 

Length

Max length8
Median length7
Mean length5.5322581
Min length4

Characters and Unicode

Total characters5145
Distinct characters36
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowApple
2nd rowApple
3rd rowApple
4th rowApple
5th rowApple

Common Values

ValueCountFrequency (%)
Oppo 129
13.9%
Apple 97
10.4%
Honor 91
9.8%
Samsung 88
9.5%
Vivo 86
9.2%
Realme 69
7.4%
Motorola 62
 
6.7%
Infinix 56
 
6.0%
OnePlus 53
 
5.7%
Huawei 42
 
4.5%
Other values (9) 157
16.9%

Length

2025-06-20T01:04:13.759531image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
oppo 129
13.9%
apple 97
10.4%
honor 91
9.8%
samsung 88
9.5%
vivo 86
9.2%
realme 69
7.4%
motorola 62
 
6.7%
infinix 56
 
6.0%
oneplus 53
 
5.7%
huawei 42
 
4.5%
Other values (8) 157
16.9%

Most occurring characters

ValueCountFrequency (%)
o 745
14.5%
p 452
 
8.8%
n 407
 
7.9%
e 405
 
7.9%
i 308
 
6.0%
l 302
 
5.9%
a 299
 
5.8%
O 248
 
4.8%
m 184
 
3.6%
u 183
 
3.6%
Other values (26) 1612
31.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 5145
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
o 745
14.5%
p 452
 
8.8%
n 407
 
7.9%
e 405
 
7.9%
i 308
 
6.0%
l 302
 
5.9%
a 299
 
5.8%
O 248
 
4.8%
m 184
 
3.6%
u 183
 
3.6%
Other values (26) 1612
31.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 5145
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
o 745
14.5%
p 452
 
8.8%
n 407
 
7.9%
e 405
 
7.9%
i 308
 
6.0%
l 302
 
5.9%
a 299
 
5.8%
O 248
 
4.8%
m 184
 
3.6%
u 183
 
3.6%
Other values (26) 1612
31.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 5145
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
o 745
14.5%
p 452
 
8.8%
n 407
 
7.9%
e 405
 
7.9%
i 308
 
6.0%
l 302
 
5.9%
a 299
 
5.8%
O 248
 
4.8%
m 184
 
3.6%
u 183
 
3.6%
Other values (26) 1612
31.3%
Distinct908
Distinct (%)97.6%
Missing0
Missing (%)0.0%
Memory size7.4 KiB
2025-06-20T01:04:14.089060image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length39
Median length27
Mean length14.293548
Min length2

Characters and Unicode

Total characters13293
Distinct characters64
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique888 ?
Unique (%)95.5%

Sample

1st rowiPhone 16 128GB
2nd rowiPhone 16 256GB
3rd rowiPhone 16 512GB
4th rowiPhone 16 Plus 128GB
5th rowiPhone 16 Plus 256GB
ValueCountFrequency (%)
128gb 314
 
10.6%
256gb 275
 
9.3%
pro 243
 
8.2%
5g 149
 
5.0%
galaxy 88
 
3.0%
512gb 84
 
2.8%
64gb 82
 
2.8%
iphone 80
 
2.7%
pad 54
 
1.8%
oneplus 53
 
1.8%
Other values (374) 1545
52.1%
2025-06-20T01:04:14.565934image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2037
15.3%
G 1072
 
8.1%
2 869
 
6.5%
B 778
 
5.9%
1 721
 
5.4%
5 654
 
4.9%
o 634
 
4.8%
P 547
 
4.1%
a 487
 
3.7%
6 451
 
3.4%
Other values (54) 5043
37.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 13293
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
2037
15.3%
G 1072
 
8.1%
2 869
 
6.5%
B 778
 
5.9%
1 721
 
5.4%
5 654
 
4.9%
o 634
 
4.8%
P 547
 
4.1%
a 487
 
3.7%
6 451
 
3.4%
Other values (54) 5043
37.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 13293
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
2037
15.3%
G 1072
 
8.1%
2 869
 
6.5%
B 778
 
5.9%
1 721
 
5.4%
5 654
 
4.9%
o 634
 
4.8%
P 547
 
4.1%
a 487
 
3.7%
6 451
 
3.4%
Other values (54) 5043
37.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 13293
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
2037
15.3%
G 1072
 
8.1%
2 869
 
6.5%
B 778
 
5.9%
1 721
 
5.4%
5 654
 
4.9%
o 634
 
4.8%
P 547
 
4.1%
a 487
 
3.7%
6 451
 
3.4%
Other values (54) 5043
37.9%
Distinct148
Distinct (%)15.9%
Missing0
Missing (%)0.0%
Memory size7.4 KiB
2025-06-20T01:04:14.761858image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length6
Median length4
Mean length4.0107527
Min length4

Characters and Unicode

Total characters3730
Distinct characters12
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique42 ?
Unique (%)4.5%

Sample

1st row174g
2nd row174g
3rd row174g
4th row203g
5th row203g
ValueCountFrequency (%)
190g 68
 
7.3%
195g 64
 
6.9%
185g 29
 
3.1%
192g 26
 
2.8%
180g 25
 
2.7%
205g 22
 
2.4%
186g 22
 
2.4%
198g 22
 
2.4%
206g 21
 
2.3%
188g 21
 
2.3%
Other values (138) 610
65.6%
2025-06-20T01:04:15.088685image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
g 930
24.9%
1 694
18.6%
2 375
10.1%
9 355
 
9.5%
0 326
 
8.7%
8 295
 
7.9%
5 221
 
5.9%
6 147
 
3.9%
7 144
 
3.9%
4 128
 
3.4%
Other values (2) 115
 
3.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 3730
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
g 930
24.9%
1 694
18.6%
2 375
10.1%
9 355
 
9.5%
0 326
 
8.7%
8 295
 
7.9%
5 221
 
5.9%
6 147
 
3.9%
7 144
 
3.9%
4 128
 
3.4%
Other values (2) 115
 
3.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 3730
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
g 930
24.9%
1 694
18.6%
2 375
10.1%
9 355
 
9.5%
0 326
 
8.7%
8 295
 
7.9%
5 221
 
5.9%
6 147
 
3.9%
7 144
 
3.9%
4 128
 
3.4%
Other values (2) 115
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 3730
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
g 930
24.9%
1 694
18.6%
2 375
10.1%
9 355
 
9.5%
0 326
 
8.7%
8 295
 
7.9%
5 221
 
5.9%
6 147
 
3.9%
7 144
 
3.9%
4 128
 
3.4%
Other values (2) 115
 
3.1%

RAM
Categorical

Distinct11
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size7.4 KiB
8GB
308 
6GB
206 
12GB
193 
4GB
146 
3GB
34 
Other values (6)
43 

Length

Max length10
Median length3
Mean length3.2612903
Min length3

Characters and Unicode

Total characters3033
Distinct characters13
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)0.2%

Sample

1st row6GB
2nd row6GB
3rd row6GB
4th row6GB
5th row6GB

Common Values

ValueCountFrequency (%)
8GB 308
33.1%
6GB 206
22.2%
12GB 193
20.8%
4GB 146
15.7%
3GB 34
 
3.7%
16GB 31
 
3.3%
2GB 6
 
0.6%
1.5GB 2
 
0.2%
8GB / 12GB 2
 
0.2%
10GB 1
 
0.1%

Length

2025-06-20T01:04:15.184019image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
8gb 310
33.2%
6gb 206
22.1%
12gb 195
20.9%
4gb 146
15.6%
3gb 34
 
3.6%
16gb 31
 
3.3%
2gb 6
 
0.6%
1.5gb 2
 
0.2%
2
 
0.2%
10gb 1
 
0.1%

Most occurring characters

ValueCountFrequency (%)
G 932
30.7%
B 932
30.7%
8 310
 
10.2%
6 237
 
7.8%
1 230
 
7.6%
2 201
 
6.6%
4 146
 
4.8%
3 34
 
1.1%
4
 
0.1%
. 2
 
0.1%
Other values (3) 5
 
0.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 3033
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
G 932
30.7%
B 932
30.7%
8 310
 
10.2%
6 237
 
7.8%
1 230
 
7.6%
2 201
 
6.6%
4 146
 
4.8%
3 34
 
1.1%
4
 
0.1%
. 2
 
0.1%
Other values (3) 5
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 3033
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
G 932
30.7%
B 932
30.7%
8 310
 
10.2%
6 237
 
7.8%
1 230
 
7.6%
2 201
 
6.6%
4 146
 
4.8%
3 34
 
1.1%
4
 
0.1%
. 2
 
0.1%
Other values (3) 5
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 3033
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
G 932
30.7%
B 932
30.7%
8 310
 
10.2%
6 237
 
7.8%
1 230
 
7.6%
2 201
 
6.6%
4 146
 
4.8%
3 34
 
1.1%
4
 
0.1%
. 2
 
0.1%
Other values (3) 5
 
0.2%

Front Camera
Categorical

Distinct29
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size7.4 KiB
16MP
211 
32MP
207 
8MP
165 
12MP
81 
5MP
47 
Other values (24)
219 

Length

Max length34
Median length4
Mean length4.1086022
Min length3

Characters and Unicode

Total characters3821
Distinct characters34
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)0.6%

Sample

1st row12MP
2nd row12MP
3rd row12MP
4th row12MP
5th row12MP

Common Values

ValueCountFrequency (%)
16MP 211
22.7%
32MP 207
22.3%
8MP 165
17.7%
12MP 81
 
8.7%
5MP 47
 
5.1%
13MP 43
 
4.6%
12MP / 4K 36
 
3.9%
50MP 30
 
3.2%
7MP 24
 
2.6%
10MP 22
 
2.4%
Other values (19) 64
 
6.9%

Length

2025-06-20T01:04:15.310957image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
16mp 211
20.5%
32mp 208
20.2%
8mp 170
16.5%
12mp 121
11.8%
5mp 47
 
4.6%
13mp 43
 
4.2%
43
 
4.2%
4k 36
 
3.5%
50mp 30
 
2.9%
10mp 25
 
2.4%
Other values (19) 94
9.1%

Most occurring characters

ValueCountFrequency (%)
M 942
24.7%
P 942
24.7%
1 415
10.9%
2 359
 
9.4%
3 251
 
6.6%
6 222
 
5.8%
8 180
 
4.7%
98
 
2.6%
0 92
 
2.4%
5 82
 
2.1%
Other values (24) 238
 
6.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 3821
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
M 942
24.7%
P 942
24.7%
1 415
10.9%
2 359
 
9.4%
3 251
 
6.6%
6 222
 
5.8%
8 180
 
4.7%
98
 
2.6%
0 92
 
2.4%
5 82
 
2.1%
Other values (24) 238
 
6.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 3821
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
M 942
24.7%
P 942
24.7%
1 415
10.9%
2 359
 
9.4%
3 251
 
6.6%
6 222
 
5.8%
8 180
 
4.7%
98
 
2.6%
0 92
 
2.4%
5 82
 
2.1%
Other values (24) 238
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 3821
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
M 942
24.7%
P 942
24.7%
1 415
10.9%
2 359
 
9.4%
3 251
 
6.6%
6 222
 
5.8%
8 180
 
4.7%
98
 
2.6%
0 92
 
2.4%
5 82
 
2.1%
Other values (24) 238
 
6.2%
Distinct91
Distinct (%)9.8%
Missing0
Missing (%)0.0%
Memory size7.4 KiB
2025-06-20T01:04:15.445744image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length59
Median length50
Mean length9.2258065
Min length3

Characters and Unicode

Total characters8580
Distinct characters39
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique23 ?
Unique (%)2.5%

Sample

1st row48MP
2nd row48MP
3rd row48MP
4th row48MP
5th row48MP
ValueCountFrequency (%)
588
26.6%
50mp 425
19.2%
12mp 202
 
9.1%
2mp 184
 
8.3%
8mp 170
 
7.7%
48mp 130
 
5.9%
64mp 120
 
5.4%
13mp 109
 
4.9%
108mp 55
 
2.5%
16mp 38
 
1.7%
Other values (23) 190
 
8.6%
2025-06-20T01:04:15.693837image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
M 1557
18.1%
P 1519
17.7%
1281
14.9%
+ 589
 
6.9%
0 536
 
6.2%
5 449
 
5.2%
1 433
 
5.0%
2 431
 
5.0%
8 357
 
4.2%
4 262
 
3.1%
Other values (29) 1166
13.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 8580
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
M 1557
18.1%
P 1519
17.7%
1281
14.9%
+ 589
 
6.9%
0 536
 
6.2%
5 449
 
5.2%
1 433
 
5.0%
2 431
 
5.0%
8 357
 
4.2%
4 262
 
3.1%
Other values (29) 1166
13.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 8580
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
M 1557
18.1%
P 1519
17.7%
1281
14.9%
+ 589
 
6.9%
0 536
 
6.2%
5 449
 
5.2%
1 433
 
5.0%
2 431
 
5.0%
8 357
 
4.2%
4 262
 
3.1%
Other values (29) 1166
13.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 8580
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
M 1557
18.1%
P 1519
17.7%
1281
14.9%
+ 589
 
6.9%
0 536
 
6.2%
5 449
 
5.2%
1 433
 
5.0%
2 431
 
5.0%
8 357
 
4.2%
4 262
 
3.1%
Other values (29) 1166
13.6%
Distinct217
Distinct (%)23.3%
Missing0
Missing (%)0.0%
Memory size7.4 KiB
2025-06-20T01:04:15.914209image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length32
Median length28
Mean length17.589247
Min length7

Characters and Unicode

Total characters16358
Distinct characters49
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique54 ?
Unique (%)5.8%

Sample

1st rowA17 Bionic
2nd rowA17 Bionic
3rd rowA17 Bionic
4th rowA17 Bionic
5th rowA17 Bionic
ValueCountFrequency (%)
snapdragon 371
 
13.9%
mediatek 289
 
10.9%
dimensity 215
 
8.1%
gen 167
 
6.3%
qualcomm 121
 
4.5%
8 115
 
4.3%
helio 113
 
4.2%
bionic 91
 
3.4%
1 64
 
2.4%
2 54
 
2.0%
Other values (160) 1063
39.9%
2025-06-20T01:04:16.253755image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1733
 
10.6%
n 1341
 
8.2%
a 1162
 
7.1%
i 1116
 
6.8%
e 1109
 
6.8%
o 821
 
5.0%
d 661
 
4.0%
0 632
 
3.9%
m 458
 
2.8%
8 434
 
2.7%
Other values (39) 6891
42.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 16358
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1733
 
10.6%
n 1341
 
8.2%
a 1162
 
7.1%
i 1116
 
6.8%
e 1109
 
6.8%
o 821
 
5.0%
d 661
 
4.0%
0 632
 
3.9%
m 458
 
2.8%
8 434
 
2.7%
Other values (39) 6891
42.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 16358
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1733
 
10.6%
n 1341
 
8.2%
a 1162
 
7.1%
i 1116
 
6.8%
e 1109
 
6.8%
o 821
 
5.0%
d 661
 
4.0%
0 632
 
3.9%
m 458
 
2.8%
8 434
 
2.7%
Other values (39) 6891
42.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 16358
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1733
 
10.6%
n 1341
 
8.2%
a 1162
 
7.1%
i 1116
 
6.8%
e 1109
 
6.8%
o 821
 
5.0%
d 661
 
4.0%
0 632
 
3.9%
m 458
 
2.8%
8 434
 
2.7%
Other values (39) 6891
42.1%
Distinct147
Distinct (%)15.8%
Missing0
Missing (%)0.0%
Memory size7.4 KiB
2025-06-20T01:04:16.494846image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length9
Median length8
Mean length7.6806452
Min length7

Characters and Unicode

Total characters7143
Distinct characters14
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique40 ?
Unique (%)4.3%

Sample

1st row3,600mAh
2nd row3,600mAh
3rd row3,600mAh
4th row4,200mAh
5th row4,200mAh
ValueCountFrequency (%)
5,000mah 197
21.2%
5000mah 96
 
10.3%
4,500mah 46
 
4.9%
4500mah 38
 
4.1%
5,200mah 35
 
3.8%
4,000mah 24
 
2.6%
6000mah 20
 
2.2%
4,300mah 20
 
2.2%
5,500mah 19
 
2.0%
5,100mah 19
 
2.0%
Other values (137) 416
44.7%
2025-06-20T01:04:16.853089image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2065
28.9%
m 930
13.0%
A 930
13.0%
h 930
13.0%
5 617
 
8.6%
, 615
 
8.6%
4 354
 
5.0%
3 147
 
2.1%
2 134
 
1.9%
1 119
 
1.7%
Other values (4) 302
 
4.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 7143
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 2065
28.9%
m 930
13.0%
A 930
13.0%
h 930
13.0%
5 617
 
8.6%
, 615
 
8.6%
4 354
 
5.0%
3 147
 
2.1%
2 134
 
1.9%
1 119
 
1.7%
Other values (4) 302
 
4.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 7143
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 2065
28.9%
m 930
13.0%
A 930
13.0%
h 930
13.0%
5 617
 
8.6%
, 615
 
8.6%
4 354
 
5.0%
3 147
 
2.1%
2 134
 
1.9%
1 119
 
1.7%
Other values (4) 302
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 7143
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 2065
28.9%
m 930
13.0%
A 930
13.0%
h 930
13.0%
5 617
 
8.6%
, 615
 
8.6%
4 354
 
5.0%
3 147
 
2.1%
2 134
 
1.9%
1 119
 
1.7%
Other values (4) 302
 
4.2%
Distinct97
Distinct (%)10.4%
Missing0
Missing (%)0.0%
Memory size7.4 KiB
2025-06-20T01:04:17.046283image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length44
Median length40
Mean length10.637634
Min length8

Characters and Unicode

Total characters9893
Distinct characters31
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique27 ?
Unique (%)2.9%

Sample

1st row6.1 inches
2nd row6.1 inches
3rd row6.1 inches
4th row6.7 inches
5th row6.7 inches
ValueCountFrequency (%)
inches 934
49.7%
6.7 127
 
6.8%
6.5 76
 
4.0%
6.67 69
 
3.7%
6.6 64
 
3.4%
6.78 61
 
3.2%
6.1 51
 
2.7%
6.8 39
 
2.1%
6.55 22
 
1.2%
6.43 21
 
1.1%
Other values (89) 416
22.1%
2025-06-20T01:04:17.401030image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
950
9.6%
6 948
9.6%
n 948
9.6%
e 948
9.6%
i 938
9.5%
c 934
9.4%
h 934
9.4%
s 934
9.4%
. 911
9.2%
7 341
 
3.4%
Other values (21) 1107
11.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 9893
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
950
9.6%
6 948
9.6%
n 948
9.6%
e 948
9.6%
i 938
9.5%
c 934
9.4%
h 934
9.4%
s 934
9.4%
. 911
9.2%
7 341
 
3.4%
Other values (21) 1107
11.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 9893
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
950
9.6%
6 948
9.6%
n 948
9.6%
e 948
9.6%
i 938
9.5%
c 934
9.4%
h 934
9.4%
s 934
9.4%
. 911
9.2%
7 341
 
3.4%
Other values (21) 1107
11.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 9893
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
950
9.6%
6 948
9.6%
n 948
9.6%
e 948
9.6%
i 938
9.5%
c 934
9.4%
h 934
9.4%
s 934
9.4%
. 911
9.2%
7 341
 
3.4%
Other values (21) 1107
11.2%
Distinct157
Distinct (%)16.9%
Missing0
Missing (%)0.0%
Memory size7.4 KiB
2025-06-20T01:04:17.580507image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length13
Median length10
Mean length10.412903
Min length10

Characters and Unicode

Total characters9684
Distinct characters24
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique58 ?
Unique (%)6.2%

Sample

1st rowPKR 224,999
2nd rowPKR 234,999
3rd rowPKR 244,999
4th rowPKR 249,999
5th rowPKR 259,999
ValueCountFrequency (%)
pkr 929
49.9%
79,999 39
 
2.1%
69,999 38
 
2.0%
89,999 38
 
2.0%
59,999 35
 
1.9%
54,999 32
 
1.7%
39,999 31
 
1.7%
34,999 27
 
1.5%
49,999 27
 
1.5%
64,999 27
 
1.5%
Other values (149) 637
34.2%
2025-06-20T01:04:17.883257image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9 3121
32.2%
930
 
9.6%
P 929
 
9.6%
R 929
 
9.6%
, 929
 
9.6%
K 929
 
9.6%
0 391
 
4.0%
4 350
 
3.6%
1 279
 
2.9%
2 229
 
2.4%
Other values (14) 668
 
6.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 9684
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
9 3121
32.2%
930
 
9.6%
P 929
 
9.6%
R 929
 
9.6%
, 929
 
9.6%
K 929
 
9.6%
0 391
 
4.0%
4 350
 
3.6%
1 279
 
2.9%
2 229
 
2.4%
Other values (14) 668
 
6.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 9684
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
9 3121
32.2%
930
 
9.6%
P 929
 
9.6%
R 929
 
9.6%
, 929
 
9.6%
K 929
 
9.6%
0 391
 
4.0%
4 350
 
3.6%
1 279
 
2.9%
2 229
 
2.4%
Other values (14) 668
 
6.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 9684
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
9 3121
32.2%
930
 
9.6%
P 929
 
9.6%
R 929
 
9.6%
, 929
 
9.6%
K 929
 
9.6%
0 391
 
4.0%
4 350
 
3.6%
1 279
 
2.9%
2 229
 
2.4%
Other values (14) 668
 
6.9%
Distinct147
Distinct (%)15.8%
Missing0
Missing (%)0.0%
Memory size7.4 KiB
2025-06-20T01:04:18.137560image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.093548
Min length9

Characters and Unicode

Total characters9387
Distinct characters15
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique54 ?
Unique (%)5.8%

Sample

1st rowINR 79,999
2nd rowINR 84,999
3rd rowINR 89,999
4th rowINR 89,999
5th rowINR 94,999
ValueCountFrequency (%)
inr 930
50.0%
29,999 35
 
1.9%
39,999 31
 
1.7%
22,999 30
 
1.6%
44,999 29
 
1.6%
34,999 27
 
1.5%
14,999 27
 
1.5%
24,999 26
 
1.4%
19,999 24
 
1.3%
54,999 23
 
1.2%
Other values (138) 678
36.5%
2025-06-20T01:04:18.431078image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9 2886
30.7%
, 933
 
9.9%
I 930
 
9.9%
N 930
 
9.9%
R 930
 
9.9%
930
 
9.9%
1 396
 
4.2%
4 364
 
3.9%
0 283
 
3.0%
2 282
 
3.0%
Other values (5) 523
 
5.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 9387
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
9 2886
30.7%
, 933
 
9.9%
I 930
 
9.9%
N 930
 
9.9%
R 930
 
9.9%
930
 
9.9%
1 396
 
4.2%
4 364
 
3.9%
0 283
 
3.0%
2 282
 
3.0%
Other values (5) 523
 
5.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 9387
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
9 2886
30.7%
, 933
 
9.9%
I 930
 
9.9%
N 930
 
9.9%
R 930
 
9.9%
930
 
9.9%
1 396
 
4.2%
4 364
 
3.9%
0 283
 
3.0%
2 282
 
3.0%
Other values (5) 523
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 9387
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
9 2886
30.7%
, 933
 
9.9%
I 930
 
9.9%
N 930
 
9.9%
R 930
 
9.9%
930
 
9.9%
1 396
 
4.2%
4 364
 
3.9%
0 283
 
3.0%
2 282
 
3.0%
Other values (5) 523
 
5.6%
Distinct137
Distinct (%)14.7%
Missing0
Missing (%)0.0%
Memory size7.4 KiB
2025-06-20T01:04:18.621810image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length11
Median length9
Mean length8.9075269
Min length7

Characters and Unicode

Total characters8284
Distinct characters17
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique39 ?
Unique (%)4.2%

Sample

1st rowCNY 5,799
2nd rowCNY 6,099
3rd rowCNY 6,499
4th rowCNY 6,199
5th rowCNY 6,499
ValueCountFrequency (%)
cny 929
50.0%
2,499 36
 
1.9%
1,499 32
 
1.7%
3,499 31
 
1.7%
2,199 29
 
1.6%
999 29
 
1.6%
1,799 29
 
1.6%
1,199 26
 
1.4%
2,299 25
 
1.3%
2,999 25
 
1.3%
Other values (127) 668
35.9%
2025-06-20T01:04:18.935982image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9 1909
23.0%
C 929
11.2%
Y 929
11.2%
929
11.2%
N 929
11.2%
, 876
10.6%
1 388
 
4.7%
2 302
 
3.6%
4 228
 
2.8%
0 187
 
2.3%
Other values (7) 678
 
8.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 8284
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
9 1909
23.0%
C 929
11.2%
Y 929
11.2%
929
11.2%
N 929
11.2%
, 876
10.6%
1 388
 
4.7%
2 302
 
3.6%
4 228
 
2.8%
0 187
 
2.3%
Other values (7) 678
 
8.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 8284
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
9 1909
23.0%
C 929
11.2%
Y 929
11.2%
929
11.2%
N 929
11.2%
, 876
10.6%
1 388
 
4.7%
2 302
 
3.6%
4 228
 
2.8%
0 187
 
2.3%
Other values (7) 678
 
8.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 8284
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
9 1909
23.0%
C 929
11.2%
Y 929
11.2%
929
11.2%
N 929
11.2%
, 876
10.6%
1 388
 
4.7%
2 302
 
3.6%
4 228
 
2.8%
0 187
 
2.3%
Other values (7) 678
 
8.2%
Distinct107
Distinct (%)11.5%
Missing0
Missing (%)0.0%
Memory size7.4 KiB
2025-06-20T01:04:19.151943image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length10
Median length7
Mean length7.3387097
Min length6

Characters and Unicode

Total characters6825
Distinct characters16
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique34 ?
Unique (%)3.7%

Sample

1st rowUSD 799
2nd rowUSD 849
3rd rowUSD 899
4th rowUSD 899
5th rowUSD 949
ValueCountFrequency (%)
usd 930
50.0%
499 44
 
2.4%
899 43
 
2.3%
299 43
 
2.3%
1,099 43
 
2.3%
399 42
 
2.3%
999 40
 
2.2%
199 39
 
2.1%
799 38
 
2.0%
349 37
 
2.0%
Other values (98) 561
30.2%
2025-06-20T01:04:19.509900image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9 1381
20.2%
U 930
13.6%
S 930
13.6%
D 930
13.6%
930
13.6%
1 320
 
4.7%
4 277
 
4.1%
2 254
 
3.7%
0 188
 
2.8%
3 166
 
2.4%
Other values (6) 519
 
7.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 6825
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
9 1381
20.2%
U 930
13.6%
S 930
13.6%
D 930
13.6%
930
13.6%
1 320
 
4.7%
4 277
 
4.1%
2 254
 
3.7%
0 188
 
2.8%
3 166
 
2.4%
Other values (6) 519
 
7.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 6825
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
9 1381
20.2%
U 930
13.6%
S 930
13.6%
D 930
13.6%
930
13.6%
1 320
 
4.7%
4 277
 
4.1%
2 254
 
3.7%
0 188
 
2.8%
3 166
 
2.4%
Other values (6) 519
 
7.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 6825
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
9 1381
20.2%
U 930
13.6%
S 930
13.6%
D 930
13.6%
930
13.6%
1 320
 
4.7%
4 277
 
4.1%
2 254
 
3.7%
0 188
 
2.8%
3 166
 
2.4%
Other values (6) 519
 
7.6%
Distinct141
Distinct (%)15.2%
Missing0
Missing (%)0.0%
Memory size7.4 KiB
2025-06-20T01:04:19.697962image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length10
Median length9
Mean length8.5096774
Min length7

Characters and Unicode

Total characters7914
Distinct characters15
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique47 ?
Unique (%)5.1%

Sample

1st rowAED 2,799
2nd rowAED 2,999
3rd rowAED 3,199
4th rowAED 3,199
5th rowAED 3,399
ValueCountFrequency (%)
aed 930
50.0%
1,499 39
 
2.1%
1,099 35
 
1.9%
1,299 29
 
1.6%
3,299 25
 
1.3%
1,699 25
 
1.3%
999 24
 
1.3%
699 23
 
1.2%
1,899 23
 
1.2%
899 23
 
1.2%
Other values (132) 684
36.8%
2025-06-20T01:04:20.022877image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9 1638
20.7%
A 930
11.8%
E 930
11.8%
D 930
11.8%
930
11.8%
, 701
8.9%
1 434
 
5.5%
0 275
 
3.5%
4 241
 
3.0%
2 230
 
2.9%
Other values (5) 675
8.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 7914
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
9 1638
20.7%
A 930
11.8%
E 930
11.8%
D 930
11.8%
930
11.8%
, 701
8.9%
1 434
 
5.5%
0 275
 
3.5%
4 241
 
3.0%
2 230
 
2.9%
Other values (5) 675
8.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 7914
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
9 1638
20.7%
A 930
11.8%
E 930
11.8%
D 930
11.8%
930
11.8%
, 701
8.9%
1 434
 
5.5%
0 275
 
3.5%
4 241
 
3.0%
2 230
 
2.9%
Other values (5) 675
8.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 7914
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
9 1638
20.7%
A 930
11.8%
E 930
11.8%
D 930
11.8%
930
11.8%
, 701
8.9%
1 434
 
5.5%
0 275
 
3.5%
4 241
 
3.0%
2 230
 
2.9%
Other values (5) 675
8.5%

Launched Year
Real number (ℝ)

Distinct11
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2022.1935
Minimum2014
Maximum2025
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.4 KiB
2025-06-20T01:04:20.129680image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum2014
5-th percentile2019
Q12021
median2023
Q32024
95-th percentile2024
Maximum2025
Range11
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.8620802
Coefficient of variation (CV)0.00092082194
Kurtosis0.65705415
Mean2022.1935
Median Absolute Deviation (MAD)1
Skewness-0.96323126
Sum1880640
Variance3.4673426
MonotonicityNot monotonic
2025-06-20T01:04:20.241012image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
2024 292
31.4%
2023 184
19.8%
2022 149
16.0%
2021 109
 
11.7%
2020 101
 
10.9%
2019 46
 
4.9%
2018 21
 
2.3%
2025 12
 
1.3%
2017 9
 
1.0%
2016 5
 
0.5%
ValueCountFrequency (%)
2014 2
 
0.2%
2016 5
 
0.5%
2017 9
 
1.0%
2018 21
 
2.3%
2019 46
 
4.9%
2020 101
 
10.9%
2021 109
 
11.7%
2022 149
16.0%
2023 184
19.8%
2024 292
31.4%
ValueCountFrequency (%)
2025 12
 
1.3%
2024 292
31.4%
2023 184
19.8%
2022 149
16.0%
2021 109
 
11.7%
2020 101
 
10.9%
2019 46
 
4.9%
2018 21
 
2.3%
2017 9
 
1.0%
2016 5
 
0.5%

Interactions

2025-06-20T01:04:13.004831image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Correlations

2025-06-20T01:04:20.318285image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Company NameFront CameraLaunched YearRAM
Company Name1.0000.3870.2300.162
Front Camera0.3871.0000.2550.255
Launched Year0.2300.2551.0000.362
RAM0.1620.2550.3621.000

Missing values

2025-06-20T01:04:13.249591image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
A simple visualization of nullity by column.
2025-06-20T01:04:13.434267image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

Company NameModel NameMobile WeightRAMFront CameraBack CameraProcessorBattery CapacityScreen SizeLaunched Price (Pakistan)Launched Price (India)Launched Price (China)Launched Price (USA)Launched Price (Dubai)Launched Year
0AppleiPhone 16 128GB174g6GB12MP48MPA17 Bionic3,600mAh6.1 inchesPKR 224,999INR 79,999CNY 5,799USD 799AED 2,7992024
1AppleiPhone 16 256GB174g6GB12MP48MPA17 Bionic3,600mAh6.1 inchesPKR 234,999INR 84,999CNY 6,099USD 849AED 2,9992024
2AppleiPhone 16 512GB174g6GB12MP48MPA17 Bionic3,600mAh6.1 inchesPKR 244,999INR 89,999CNY 6,499USD 899AED 3,1992024
3AppleiPhone 16 Plus 128GB203g6GB12MP48MPA17 Bionic4,200mAh6.7 inchesPKR 249,999INR 89,999CNY 6,199USD 899AED 3,1992024
4AppleiPhone 16 Plus 256GB203g6GB12MP48MPA17 Bionic4,200mAh6.7 inchesPKR 259,999INR 94,999CNY 6,499USD 949AED 3,3992024
5AppleiPhone 16 Plus 512GB203g6GB12MP48MPA17 Bionic4,200mAh6.7 inchesPKR 274,999INR 104,999CNY 6,999USD 999AED 3,5992024
6AppleiPhone 16 Pro 128GB206g6GB12MP / 4K50MP + 12MPA17 Pro4,400mAh6.1 inchesPKR 284,999INR 99,999CNY 6,999USD 999AED 3,4992024
7AppleiPhone 16 Pro 256GB206g8GB12MP / 4K50MP + 12MPA17 Pro4,400mAh6.1 inchesPKR 294,999INR 104,999CNY 7,099USD 1,049AED 3,6992024
8AppleiPhone 16 Pro 512GB206g8GB12MP / 4K50MP + 12MPA17 Pro4,400mAh6.1 inchesPKR 314,999INR 114,999CNY 7,499USD 1,099AED 3,8992024
9AppleiPhone 16 Pro Max 128GB221g6GB12MP / 4K48MP + 12MPA17 Pro4,500mAh6.7 inchesPKR 314,999INR 109,999CNY 7,499USD 1,099AED 3,7992024
Company NameModel NameMobile WeightRAMFront CameraBack CameraProcessorBattery CapacityScreen SizeLaunched Price (Pakistan)Launched Price (India)Launched Price (China)Launched Price (USA)Launched Price (Dubai)Launched Year
920POCOF6 Pro 256GB210g8GB20MP108MPSnapdragon 8+ Gen 25160mAh6.67 inchesPKR 109,999INR 44,999CNY 3,499USD 549AED 1,9992024
921POCOC65 64GB190g4GB5MP50MPMediaTek Helio G855000mAh6.5 inchesPKR 24,999INR 10,999CNY 999USD 149AED 5992024
922POCOX7 128GB195g6GB16MP64MPMediaTek Dimensity 82005000mAh6.67 inchesPKR 64,999INR 22,999CNY 2,199USD 329AED 1,1992025
923POCOX7 Pro 256GB207g8GB20MP108MPMediaTek Dimensity 84006000mAh6.67 inchesPKR 79,999INR 27,999CNY 2,699USD 399AED 1,4992025
924POCOM7 5G 128GB198g6GB8MP50MPMediaTek Dimensity 70255110mAh6.67 inchesPKR 39,999INR 15,999CNY 1,599USD 229AED 8992024
925PocoPad 5G 128GB571g8GB8MP8MPSnapdragon 7s Gen 210,000mAh12.1 inchesPKR 66,220INR 23,999CNY 2,099USD 280AED 1,0292024
926PocoPad 5G 256GB571g8GB8MP8MPSnapdragon 7s Gen 210,000mAh12.1 inchesPKR 71,220INR 25,999CNY 2,299USD 300AED 1,0992024
927SamsungGalaxy Z Fold6 256GB239g12GB10MP, 4MP (UDC)50MPSnapdragon 8 Gen 34400mAh7.6 inchesPKR 604,999INR 164,999¥13,999USD 1,899AED 7,1992024
928SamsungGalaxy Z Fold6 512GB239g12GB10MP, 4MP (UDC)50MPSnapdragon 8 Gen 34400mAh7.6 inchesPKR 544,999INR 176,999CNY 15,999USD 1719AED 7,6992024
929SamsungGalaxy Z Fold6 1TB239g12GB10MP, 4MP (UDC)50MPSnapdragon 8 Gen 34400mAh7.6 inchesNot availableINR 200,999CNY 17,999USD 2,259AED 8,6992024

Duplicate rows

Most frequently occurring

Company NameModel NameMobile WeightRAMFront CameraBack CameraProcessorBattery CapacityScreen SizeLaunched Price (Pakistan)Launched Price (India)Launched Price (China)Launched Price (USA)Launched Price (Dubai)Launched Year# duplicates
0InfinixHot 10 Lite 64GB195g3GB8MP13MPMediaTek Helio A255,000mAh6.6 inchesPKR 19,999INR 7,999CNY 699USD 109AED 39920202
1OppoA3 128GB186g4GB5MP50MPSnapdragon 6s 4G Gen 15000mAh6.7 inchesPKR 59,999INR 34,999CNY 2,999USD 399AED 1,49920242
2OppoK10 5G 128GB205g8GB16MP64MP + 8MP + 2MPMediaTek Dimensity 8000-Max5,000mAh6.59 inchesPKR 64,999INR 19,999CNY 1,799USD 249AED 1,30020222
3OppoK10x 128GB195g6GB16MP64MP + 2MP + 2MPQualcomm Snapdragon 6955,000mAh6.59 inchesPKR 54,999INR 16,990CNY 1,499USD 199AED 1,00020222
4OppoK10x 256GB195g8GB16MP64MP + 2MP + 2MPQualcomm Snapdragon 6955,000mAh6.59 inchesPKR 59,999INR 18,990CNY 1,699USD 229AED 1,20020222
5OppoK11x 128GB195g8GB16MP108MP + 2MPQualcomm Snapdragon 6955,000mAh6.72 inchesPKR 59,999INR 18,000CNY 1,499USD 199AED 1,00020232
6OppoK11x 256GB195g12GB16MP108MP + 2MPQualcomm Snapdragon 6955,000mAh6.72 inchesPKR 64,999INR 20,000CNY 1,699USD 229AED 1,20020232
7OppoK7 5G 128GB180g8GB32MP48MP + 8MP + 2MP + 2MPQualcomm Snapdragon 765G4,025mAh6.4 inchesPKR 49,999INR 19,999CNY 1,999USD 279AED 1,40020202
8OppoK7x 128GB194g6GB16MP48MP + 8MP + 2MP + 2MPMediaTek Dimensity 7205,000mAh6.5 inchesPKR 44,999INR 14,999CNY 1,499USD 199AED 1,00020202
9OppoK9 5G 128GB172g8GB32MP64MP + 8MP + 2MPQualcomm Snapdragon 768G4,300mAh6.43 inchesPKR 59,999INR 22,999CNY 1,999USD 279AED 1,40020212